code: def transform(self, X, y=None):
      if isinstance(X, dict):
          for col, col_dict in self.column_ranges.items():
              if col in X:
                  X[col] = scale_val(
                      val=X[col],
                      min_val=col_dict["min_val"],
                      total_range=col_dict["inner_range"],
                      truncate_large_values=self.truncate_large_values,
                  )
      else:
          if len(self.cols_to_ignore) > 0:
              X = utils.safely_drop_columns(X, self.cols_to_ignore)
  
          for col, col_dict in self.column_ranges.items():
              if col in X.columns:
                  min_val = col_dict["min_val"]
                  inner_range = col_dict["inner_range"]
                  X[col] = X[col].apply(
                      lambda x: scale_val(
                          x,
                          min_val,
                          inner_range,
                          self.truncate_large_values,
                      )
                  )
  
      return X
  
file_path: auto_ml/auto_ml/utils_scaling.py
imports: from sklearn.base import BaseEstimator, TransformerMixin
  from auto_ml import utils
label_desc: Use image node_id 4 for calling the CustomSparseScaler obj's underlying member method code with example usage: obj.transform(X, y) and returns: X